Abstract Few interventions have been shown to be as beneficial to human health as physical exercise, yet we remain largely ignorant of the mechanisms by which those potent effects are transduced. The Molecular Transducers of Physical Activity Consortium will examine the response to acute and chronic exercise at multiple scales and in multiple tissues across thousands of humans and in animal models. The study will combine state of the art phenotyping with molecular omics approaches. Building on our long history of analytical innovation in high throughput biology and experience in the analysis of perhaps the largest multi- omic study funded to date, the Stanford MoTrPAC Bioinformatics Center will provide core compute, storage and analytic expertise to the MoTrPAC investigators. Taking advantage of our close links with the Stanford high performance computing center and the Google cloud engineering team, we will build a platform for the secure sharing of time-series, training-related, multi-omic, physiological and sensor based measurement data. Aim 1 is focused on creating a local test computing environment and a cloud-based data warehouse for raw data. We will achieve this by first establishing standards for data security and privacy, protocols for data sharing, and a common data element dictionary. Aim 2 describes both the extension of existing omics pipelines and the development of new pipelines for raw multi-omic data. In addition, we propose the development of novel analytic approaches for multi-scale, high-throughput data. Building on expertise from Stanford's renowned statistics department as well as the new department of Biomedical Data Science, we will extend graph based approaches developed by our team into the time dimension across multiple data sets to understand the systems biology of the response to physical training at a fundamental level. In addition, we will focus on data integration and novel visualization approaches. Aim 3 is concerned with building an interactive interface for investigators and participants to interrogate, interact with, explore, and securely download the data. Aim 4 will look outside of MoTrPAC to broader integration with relevant datasets such as GTeX, GEO, the Precision Medicine Cohort, the UK Biobank and others. We believe our team's direct experience in the leadership of studies such as the Undiagnosed Diseases Network, ENCODE, ClinGen, BD2K (Mobilize Center), and MyHeart Counts (one of the launch applications for Apple's ResearchKit framework) will be advantageous in maximizing the benefit of MoTrPAC for investigators around the world.